Effects of Soil Parameter Variabilities on the Estimation of Ground‐Motion Amplification Factors
Bibliographic record
Abstract
Ground‐motion amplification factors (GMAFs) are used to characterize amplification of a ground motion propagating from the bedrock to the ground surface. They are usually determined by ground response analysis, in which the soil parameter variabilities and input motion uncertainties contribute to their uncertainty. The construction of design response spectra requires mean GMAFs or GMAFs with different probability levels. Thus, it is significant to study the sensitivity of soil parameter variabilities and the number of random soil profiles for the estimation of GMAFs. This study investigates the minimum number of random soil profiles required to represent the extent of the epistemic uncertainty in the GMAFs obtained from ground response analysis. It shows that at least 20 and 60 random soil profiles are respectively required to estimate the mean and standard deviations of GMAFs with the maximum relative difference below 10%. In addition, potential reasons for a reduction in the mean GMAFs resulting from randomization of the soil column properties are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".